Over 3 000 Mozambican smallholder farmers supply cassava to Company XYZ. XYZ needs an effective supplier segmentation method to gain insight into how it should direct its resources for the greatest impact. This paper describes the application of the k-means algorithm, agglomerative hierarchical clustering, and a self-organising map with ward clustering to segment these cassava suppliers. The insights gained from the cluster analysis are then used to provide recommendations and suggest suitable intervention strategies to manage each segment of suppliers. The proposed method offers users the basis of a supplier segmentation system that is more robust than commonly used qualitative supplier segmentation models.